In general, development of a hardware product is a work for determining many design specifications and manufacture specifications so as to satisfy a function required in a product. For example, in the case of an assembly product such as a mechanical appliance, shapes and materials of respective parts, manufacturing methods of the parts (manufacturing procedures, manufacturing apparatuses used in respective steps, usage conditions of the manufacturing apparatuses, and the like), assembly methods of the parts, and the like are determined. Also, in the case of a thin film process product typified by a semiconductor LSI, a circuit satisfying a required function, a manufacturing method of a mask represented with pattern information of two-dimensional binary data in order to transfer its electrical circuit information onto a semiconductor device (a producing method of mask data or the like), and a manufacturing method of a thin film process (a manufacturing procedure, manufacturing apparatuses used in respective steps, usage conditions of the manufacturing apparatuses, and the like) are determined.
Evaluating methods, analyzing methods and optimizing methods of the design specifications and supporting methods thereof have been conventionally proposed for efficiently determining many design specifications in a hardware product.
For example, in Taguchi method which is one of methods of experiment design, a table called “orthogonal table” where levels of respective columns appear evenly is used to determine a design parameter to be a control factor and its level range, and experiments based upon the orthogonal table are performed. By this means, a proper value of a design parameter capable of minimizing a variation in product function and satisfying a target specification can be obtained. For example, the Taguchi method is described in detail in “design of experiments” by Shu Yamada, JUSE Press, Ltd. ISBN4-8171-0389-2 (Non-Patent Document 1). In this case, when one control factor of eight control factors is set to two levels and the remaining seven control factors are set to three levels, the total number of combinations becomes 21×37=4374, which requires many experiments.
On the other hand, in Taguchi method, when an orthogonal table called “L18” is used, it is only necessary to perform eighteen patterns of experiments. Since the number of times of experiments which can be performed actually is limited, it is necessary to extract design parameters which have relatively little interrelationship and influence product functions from all design parameters to allocate them to the orthogonal table. Further, in an experiment, an appropriate value of a design parameter robust to the function variation can be obtained by adding an error factor (for example, environmental condition, change in time, and the like) which is a parameter which influences a function of a product but is practically difficult to control and change.
Japanese Patent Application Laid-Open Publication No. 5-41443 (Patent Document 1) has proposed an analyzing system for a product specification, in which an optimal value of a design parameter (for example, shape and material) of a product is calculated based upon comprehensive judgment from a plurality of evaluation indexes. In this technology, regarding a plurality of evaluation items, analysis is performed while changing a design parameter within a preliminarily inputted predetermined range by using an evaluation program stored in the system. Then, the analysis results of the plurality of evaluation items are converted to a single evaluation index based on a predetermined evaluation function, thereby determining an optimal design parameter value.
Also, Japanese Patent Application Laid-Open Publication No. 7-200662 (Patent Document 2) has proposed an experiment design supporting system, in which product failures in the past product developments are accumulated and analysis and experiment designs are efficiently prepared by using this information in the event of a novel product design. In this system, correspondence relationships between product failures caused in the past product development processes and the causes of the occurrences thereof and between the product failures and design parameters at the time of failure occurrence are accumulated. At the time of the design of a novel product, the past products with the specification similar to the product specification of the new product are extracted, and the cause and process of the occurrence of the product failure are displayed.
Further, Japanese Patent Application Laid-Open Publication No. 2000-148817 (Patent Document 3) has proposed a designing method using a neural network method so as to readily coordinate a plurality of design parameters. In this designing method, a neural network in which a plurality of design parameters are set in an input layer and product functions are set in an output layer is first established. Then, measurement values of product functions obtained when the plurality of design parameters are actually changed are inputted to this network, and the network is caused to learn a mapping relationship between design parameter inputs and product function outputs. Further, an adjustment network in which design parameters for adjustment are set in an input layer and the remaining design parameters are set in an output layer is provided at a former stage of the neural network, and coupling load of the adjustment network is adjusted so as to minimize an objective function of an estimated error between an estimation value of a product function estimated by using the mapping relationship between the design parameter and the product function and an actual measurement result. By this means, an optimum solution of the design parameter is derived.
Also, Japanese Patent Application Laid-Open Publication No. 2002-259464 (Patent Document 4) has proposed a supporting apparatus for a method of experiment design, which comprises: means for selecting a control factor and an error factor to be allocated to an orthogonal table from candidates displayed on a screen; and means for separately displaying selected factors and the other factors in order to efficiently perform the planning of an experiment design using a method of experiment design such as the above-described Taguchi method without fail.
Further, Japanese Patent No. 3313040 (Patent Document 5) has proposed a design supporting system, in which an estimation expression representing a relationship between a characteristic value to be analyzed and a design parameter is prepared through variance analysis using an orthogonal table, and setting of a design parameter and calculation of a reliability evaluation index can be performed through the arithmetic optimizing calculation using this estimation expression.
This system comprises: means for allocating design parameters to an orthogonal table; means for performing an experiment or structure analysis based upon the orthogonal table; means for performing variance analysis of the result; influence degree analyzing means including means for preparing an estimation expression for a characteristic value to be analyzed based upon the variance analysis result; means for performing arithmetic optimizing calculation using the prepared estimation expression; and means for calculating an evaluation index of reliability according to a probabilistic and statistic method after the optimizing calculation.